Nicolai Ort
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73 lines
1.8 KiB
Markdown
73 lines
1.8 KiB
Markdown
---
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title: "The auto-scaling part: VPA, HPQ, KEDA, Nodes, How do they dance"
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weight: 10
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tags:
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- rejekts
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---
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{{% button href="https://www.youtube.com/watch?v=1US_-3udMDo" style="warning" icon="video" %}}Watch talk on YouTube{{% /button %}}
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<!-- {{% button href="https://docs.google.com/presentation/d/1nEK0CVC_yQgIDqwsdh-PRihB6dc9RyT-" style="tip" icon="person-chalkboard" %}}Slides{{% /button %}} -->
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## Hypothesis
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- In 2024 27% of cloud spent was wasted
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- 100ms delay => decrease in sales
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## Pod resources
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- Requests: Informs scheduler's decision
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- Too low: Schedule on strained nodes
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- Too high: Wasted resources
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- Limits: Throttels (CPU) or Kills (Memory) if reached
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- QoS: sort the eviction priority during ressource pressure
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- Quranteed (request=limits)
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- Burstable (Limits>Requests)
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- Best effort (Nothing defined)
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- Gotcha: CPU throtteling can happen before tirggers happen if requests and limits are very close
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TODO: Steal table from Slides
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Requests | 100m, 256Mi | 100m, 256Mi
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Limits |100m, 256Mi | None or <limits
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QoS | Gurantee | Burstable | Best effort
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## Scalers
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- VPA: Moar power aka reccomend requests
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- HPA: Moar moar aka more replicas
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- KEDA: Proxy over HPA
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### VPA
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Modes:
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- Off: Dry-Run
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- Initial: Applies Reccomendations to new Pods (can be used for finding out)
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- Auto/Recreate: Evicts and restarts pods to update resources
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Trigger: Usually Memory
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Tip: `maxAllowed` in order to not exhaust stuff
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### HPA
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- Trigger: Usually cpu (percent of requests)
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- Formula: $1+\frac{usage}{target}$
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- Fun fact: Can not scale to 0
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### KeDA
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- Basicly automates HPA with flexible metrics (from different soruces)
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- Can scale Jobs
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- Can Scale to 0
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## Anti patterns
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TODO: Steal from slides
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| Pattern | Bad | Better
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| CPI limit = Requests | Throtteling before scale | Set requests only |
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## Demo
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Auto scaling meme generator (see slides/video) |